System and method for hydrocarbon production forecasting

ABSTRACT

A system and method for hydrocarbon production forecasting which includes creating an integrated production model representative of at least two interconnected subsurface tanks, at least one well, and a surface network, wherein the surface network comprises multiple components including at least one pipeline; parameterizing a subsurface part of the integrated production model by using material balance to characterize the at least two interconnected subsurface tanks; parameterizing a well part of the integrated production model based in part on well geometry; parameterizing the surface network based on the multiple components of the surface network; combining the parameterized subsurface part, the parameterized well part and the parameterized surface network into an improved integrated production model; forecasting hydrocarbon production based on the improved integrated production model and displaying the input, output and intermediary products.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Patent Application Ser. No.61/501,628 with a filing date of Jun. 27, 2011.

FIELD OF THE INVENTION

The present invention relates generally to methods and systems forhydrocarbon production forecasting and, in particular, methods andsystems for creating an integrated production model for hydrocarbonproduction forecasting.

BACKGROUND OF THE INVENTION

Production forecasting involves attaching a timescale to productionrecovery and it is one of the most vital roles of reservoir engineering.It underpins the cashflow of any project and can make the differencebetween a project being sanctioned or abandoned. The complexity of therole is underscored by the requirement to integrate multiple and diversedisciplines including subsurface characterisation, surface networkconfiguration, production philosophy, economic limits, businessdecisions and operational constraints.

Unlike production forecasting for oil fields, gas forecasting is furthercomplicated by long-term contracts and the need to meet contractualobligations. This requirement means that gas companies need to correctlypredict the execution of future projects to ensure that they have enoughgas security to satisfy their contractual obligations. Usually, in gasforecasting, multiple fields with diverse fluid properties are producedsimultaneously and this further introduces the complication of gasquality and maximizing the value of by-products like condensate andnatural gas liquids. These complexities imply that an integrated gasforecasting model is required to accurately predict production for a gasfield. There are many such products available including companyproprietary software for internal use only and commercial software inthe public domain. One such commercial product is the IntegratedProduction Model (IPM) suite of software by Petroleum Experts (PETEX).

The following industry standard acronyms are used in this paper:

-   BBL=Barrel-   BHP=Bottom Hole Pressure-   dP=Pressure Drop-   F_(w)=Water fractional flow-   GAP=General Allocation Package—IPM Software-   GOR=Gas Oil Ratio-   IAM=Integrated Asset Management-   IPM=Integrated Production Model-   IPR=Inflow Performance Relationship-   LNG=Liquefied natural gas-   LPG=Liquefied Petroleum Gas-   MBAL=Material Balance—IPM Software-   MCP=Major Capital Project-   MMSCF=Million Standard Cubic Feet-   NOJV=Non-Operated Joint Venture-   NPV=Net Present Value-   PETEX=Petroleum Experts-   PV=Pore Volume-   PVT=Pressure Volume Temperature-   QC=Quality Control-   SCAL=Special Core Analysis-   Tmax=Technical Max-   VBA=Visual Basic for Applications-   VLP=Vertical Lift Performance-   WGR=Water Gas Ratio

SUMMARY OF THE INVENTION

According to one implementation of the present invention, acomputer-implemented method for characterizing a subsurface reservoir ispresented. An embodiment of the invention includes creating anintegrated production model representative of at least twointerconnected subsurface tanks, at least one well, and a surfacenetwork, wherein the surface network comprises multiple componentsincluding at least one pipeline; parameterizing a subsurface part of theintegrated production model by using material balance to characterizethe at least two interconnected subsurface tanks; parameterizing a wellpart of the integrated production model based in part on well geometry;parameterizing the surface network based on the multiple components ofthe surface network; combining the parameterized subsurface part, theparameterized well part and the parameterized surface network into animproved integrated production model; and forecasting hydrocarbonproduction based on the improved integrated production model.

Another embodiment of the invention includes a computer systemconfigured to implement executable computer modules designed to performthe steps of the method described above and to display the input, outputand intermediary products of the method.

The above summary section is provided to introduce a selection ofconcepts in a simplified form that are further described below in thedetailed description section. The summary is not intended to identifykey features or essential features of the claimed subject matter, nor isit intended to be used to limit the scope of the claimed subject matter.Furthermore, the claimed subject matter is not limited toimplementations that solve any or all disadvantages noted in any part ofthis disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of the present invention will become betterunderstood with regard to the following description, claims andaccompanying drawings where:

FIG. 1 is a schematic of the IPM of the present invention;

FIG. 2 is a flowchart illustrating a method in accordance with anotherembodiment of the present invention;

FIG. 3 is a comparison of pressure matching using a prior art IPM andthe IPM of the present invention;

FIG. 4 is a comparison of water production matching using a prior artIPM and the IPM of the present invention;

FIG. 5 demonstrates two types of separators that may be incorporated inthe IPM;

FIG. 6 graphically displays curves used to model compressors in the IPMof the present invention;

FIG. 7 illustrates calibration of the surface network part of the IPM;

FIG. 8 illustrates the impact of poor calibration of the surface networkpart on production forecasting;

FIG. 9 illustrates discrepancies in production rates that may be used tocombine parts of the IPM of the present invention;

FIG. 10 illustrates a partial IPM indicating constraints;

FIG. 11 illustrates standardized displays of production forecasting forcommunication and quality assurance purposes; and

FIG. 12 schematically illustrates a system for performing a method inaccordance with an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention may be described and implemented in the generalcontext of a system and computer methods to be executed by a computer.Such computer-executable instructions may include programs, routines,objects, components, data structures, and computer software technologiesthat can be used to perform particular tasks and process abstract datatypes. Software implementations of the present invention may be coded indifferent languages for application in a variety of computing platformsand environments. It will be appreciated that the scope and underlyingprinciples of the present invention are not limited to any particularcomputer software technology.

Moreover, those skilled in the art will appreciate that the presentinvention may be practiced using any one or combination of hardware andsoftware configurations, including but not limited to a system havingsingle and/or multiple processor computers, hand-held devices,programmable consumer electronics, mini-computers, mainframe computers,and the like. The invention may also be practiced in distributedcomputing environments where tasks are performed by servers or otherprocessing devices that are linked through a one or more datacommunications network. In a distributed computing environment, programmodules may be located in both local and remote computer storage mediaincluding memory storage devices. The present invention may also bepracticed as part of a down-hole sensor or measuring device or as partof a laboratory measuring device.

Also, an article of manufacture for use with a computer processor, suchas a CD, pre-recorded disk or other equivalent devices, may include acomputer program storage medium and program means recorded thereon fordirecting the computer processor to facilitate the implementation andpractice of the present invention. Such devices and articles ofmanufacture also fall within the spirit and scope of the presentinvention.

Referring now to the drawings, embodiments of the present invention willbe described. The invention can be implemented in numerous ways,including, for example, as a system (including a computer processingsystem), a method (including a computer implemented method), anapparatus, a computer readable medium, a computer program product, agraphical user interface, a web portal, or a data structure tangiblyfixed in a computer readable memory. Several embodiments of the presentinvention are discussed below. The appended drawings illustrate onlytypical embodiments of the present invention and therefore are not to beconsidered limiting of its scope and breadth.

The present invention relates to hydrocarbon production forecasting and,by way of example and not limitation, hydrocarbon gas productionforecasting.

FIG. 1 illustrates a flow chart of an embodiment of the invention.Method 100 begins at step 10, obtaining an initial integrated productionmodel (IPM). This initial IPM may be generated, for example, through theuse of the Integrated Production Model (IPM) suite of software byPetroleum Experts (PETEX). Alternatively, it may be built by othersoftware packages capable of representing a complete IPM. The initialIPM may also be the result of a previous implementation of the presentinvention, now being updated due to changes in at least one part of theIPM. Other methods of generating the initial IPM are possible and theprevious examples are not meant to be limiting. Any IPM from any sourcemay be used as an initial IPM for this method.

FIG. 2 presents an exemplary schematic of an IPM. The model starts atthe fields, labelled as Fields 1-7 and Source Fields, which includesubsurface tanks and wells, and terminates at the slug catcher of theonshore plant labelled LNG Plant. Each of the fields in the model isrepresented by one or more tanks depending on the complexity required toachieve an accurate representation of the sub-surface characterization.All the critical surface facilities are appropriately modelled. Forexample, all the existing and proposed topside processing facilities(Platforms 1-4, LNG Plant), compressors, flowlines and trunklines arecaptured in the model.

With a multi-disciplinary team working together on an integrated model,it is useful to assign different parts of the model to different teammembers. For example, individual reservoir (petroleum) engineers updatethe reservoir characterization, fluid properties and well models fortheir assigned fields; and facilities engineers ensure that theplatforms, compression facilities and remaining surface network are upto date with the latest field data and operational constraints. Thisconcept is valuable when assigning key responsibilities within a team.The difficulty lies in understanding how to incorporate each engineer'supdates into the model.

To reduce this problem, flowsheets are used to break up the model into“standalone” sub-models. The engineer responsible makes changes only intheir assigned area and exports changes to a partial-IPM. This partialIPM is then imported by an overall IPM-custodian during each major modelupdate. In this way, the custodian is responsible for developingforecasts while the field engineers are responsible for all their partsof the model. This has enhanced the ability of the overall IPM-custodianto debug the model and has facilitated the process of model endorsementby all stakeholders.

Referring again to FIG. 1, once the initial IPM is obtained, thesubsurface part of the IPM is parameterized at step 11A. The use ofmaterial balance (done, for example, via the PETEX program MBAL) todescribe the sub-surface characterization of the very diverse reservoirsystems that make up the asset, allows the model to keep things simplein explaining the essential features of a reservoir system. However,this simplicity comes with its limitations. One of the characteristicsof a MBAL tank model is the rapid transmission of pressure changesthroughout the system which enables it to be treated as zerodimensional. This transmission is determined in large part by thehydraulic diffusivity constant, k/Øμc. The higher this parametric group,the more rapidly pressure equilibrium is achieved and the moreapplicable MBAL becomes. So, while it may be geologically sound to use asingle tank to represent an excellently connected gas reservoir withmulti-darcy permeability, low viscosity and high compressibility; thereality is that as the reservoir volume increases the capacity torapidly transmit pressure throughout the reservoir deteriorates. Arelated limitation of an MBAL tank is that it generally determines waterproduction from the properties of the tank. Consequently, drainagepoints with observed differences in their fractional flow curves may beassigned the same fractional flow curve in MBAL for predictions. Thisdiminishes the capacity of the model to monitor or predict waterproduction in aquifer-drive reservoirs. The following examples willserve to illustrate each of these limitations and how they have beenaddressed in the model.

Error! Reference source not found. is an example of an initial poorpressure match 30 for a reservoir tank due to the limitation of MBALwhich assumes instantaneous pressure transmission within a reservoirdespite the reservoir size, labelled as prior art. This particularexample has about 2 Tcf of gas in-place with only one drainage point.Line 33 shows the historical pressure data, line 32 shows the simulatedpressure data from the prior art model, and line 31 shows the simulatedgas water contact. Note the poor match between line 33 and line 32. Thesolution to improve the history match relies on being able to introducesome pressure transient within the reservoir. At step 11A of the presentembodiment, the pressure match 37 is significantly improved by dividingthe tank into two connected tanks. Here, line 36 shows the historicalpressure data, line 35 shows the simulated pressure data from the IPM ofthe present invention, and line 34 shows the simulated gas watercontact. The match between line 36 and line 35 is much improved. Step11A of method 100 uses the transmissibility factor between the tanks asa history match tuning parameter. This configuration retains theinterconnectivity of the overall reservoir system and, more importantly,allows the development of a pressure gradient across the reservoir asexpected in a tank of this size.

Prior art methods have modelled water production by monitoring fluidcontacts, for example by entering pore volume (PV) versus depth (D)data, relative permeability curves and linking the tanks to the wellmodels. This may be done, for example, by using the industry standardsoftware MBAL, SCAL, PROSPER and GAP. This fairly obvious approach isinadequate because of two problems: fluid contacts within MBAL are notused for the calculation of fluid production unless MBAL is specificallyset up to do so and the relative permeability input to a single cellmaterial balance model is not the same as relative permeability on acore plug scale. Also, the MBAL relative permeability needs to accountfor the well location, perforation depth and reservoir heterogeneity. Inorder to appropriately model water production, it is necessary toparameterize the well part of the IPM, shown in FIG. 1 as step 11B.

As explained earlier, the default setting in MBAL is that a well usesthe relative permeability of the tank to which it is connected. Thisimplies that all the wells connected to the same tank will, by default,produce the same proportion of each fluid phase regardless ofdifferences in well location and reservoir properties. To account forthe difference in water production between wells, the present embodimentemploys two different approaches depending on the well geometry.

For horizontal wells, the present embodiment overrides the defaultmethod of calculating water production from MBAL and links the waterproduction directly to the contact movement. In an aquifer drive gasreservoir system, the flood front is unconditionally stable because thevery low gas viscosity ensures that the end-point mobility ratio forwater displacing gas is so low that it dominates the influences ofheterogeneity and gravity. In this scenario there is little waterproduction until the contact reaches the perforations at which point thewater production increases exponentially until the wells fail due toliquid loading. This is modelled by enabling the monitor contacts optionin MBAL and defining an abandonment contact depth for each well based onthe perforation depths. In GAP, the implementation has an identicalintent but its implementation is slightly more complicated because GAPdoes not have the ability to abandon wells based on the contact depth.To overcome this problem, a water breakthrough depth is defined for eachwell at the perforation depth, the ‘Shift Rel Perm to Breakthrough’option is set to ‘No’, and the abandonment constraint is set to a lowwater-gas ratio (WGR) slightly higher than the condensation WGR. In oneembodiment, 5 bbl/MMscf was determined to be adequate but this is notintended to be limiting. This set up prevents the production of freewater until the contact reaches the perforation depth. When this occursthere is a step change in free water production that triggers theabandonment WGR constraint and shuts in the well.

The second approach is used for the case where there is a gradualincrease in water production with time, which is usually the situationwith vertical or deviated wells. This approach depends on having freewater production data per well that are either measured or derived froma representative reservoir simulation model. The first step is togenerate individual fractional flow curves for each well by using the‘Fw Matching’ option and regressing against the actual (or simulated)water production. If there is no historical (or simulated) free waterproduction from a well, then a fractional flow curve from an analogouswell with water production can be utilized. The fractional flow curve iscopied from the analogous well to the well without water production andthen the breakthrough saturation is modified to delay the onset of waterproduction, with an estimate of the breakthrough saturation being madeon the basis of the well location and data from other wells in thefield. Error! Reference source not found. shows a markedly improvedwater production match when using individual fractional flow curve perwell instead of the default MBAL approach of assigning the samefractional flow curve to all wells in the same tank. In FIG. 4, theinput data from 3 wells is seen as line 41, line 42, and line 43 in boththe prior art case on the left and the present embodiment on the right.The prior art uses the same fractional flow curve 40 for all wells whilethe present embodiment uses individual curves 44, 45, and 46. Thepresent embodiment matches the historical data much better. Thisfractional flow information is stored in the history wells in MBAL asrelative permeability curves. For forecasting purposes, it is necessaryto copy the data from the MBAL history wells to either the MBALprediction wells or the GAP wells (depending on the tool used forprediction). This is usually a manual exercise but there isfunctionality in GAP that allows relative permeability curves to becopied from MBAL wells to wells in GAP.

In addition to GAP and MBAL, it is possible to use PROSPER as part ofstep 11B of method 100. PROSPER is the part of the Integrated ProductionModelling toolkit that handles well performance, design andoptimization. It is designed to allow the construction of reliable andconsistent well models and has the capability to incorporate each aspectof the well bore modelling including fluid characterization (PVT),inflow performance relationship (IPR) and pressure losses along tubingand flowlines (VLP). However, there are multiple challenges in usingPROSPER especially for modelling big bore or high rate wells that arecapable of producing in excess of 300 MMscf/d. These problems include alack of well test data because of limitations in the size of the testseparators available on the platforms, location of permanent downholegauges relatively high above the perforations resulting in extrapolationerrors in bottom hole pressures (BHP), possibility of the VLP-predictedBHP to be higher than the reservoir pressure resulting in a non-physicalsituation an apparent lack of transparency in ensuring consistency inthe well models between the different software (PROSPER, MBAL and GAP).These difficulties will be addressed when step 12 of method 100 isdescribed.

At step 11C of method 100, the surface network is parameterized. Thismay be done, for example, using GAP. GAP may also be used to integratethe subsurface and wells with the surface (pipelines, separators andcompressors) elements. Due to the level of integration in GAP, decisionsin one area of the model can have implications on other areas. Oneexample of this is in modelling intermediate separators within a GAPmodel. Modelling these as inline separators rather than fixed pressureseparators increases the flexibility to appropriately respond to futurechanges in conditions anywhere in the model. However, modellingseparators as inline itself has flow on effects to other areas of themodel, particularly the calibration of pipelines. Proper calibration ismuch more important with upstream inline separators than it is withfixed pressure separators. Another area where the interdependencybetween model elements (including wells and pipeline constraints) cancause problems is in modelling compressors. The following examples willillustrate these issues.

There are two types of separator models available in GAP—fixed pressureand inline (floating) separators. Fixed pressure separators allowpressure discontinuities between the separator inlet and the outletstreams. To avoid non-physical situations where production flows from alower inlet pressure node to a higher outlet pressure node, fixedseparators should be used only at the boundary of a network system.Unfortunately, prior art methods use fixed separators within theproduction network to minimize observed convergence problems and reducethe simulation run time. A further quality check (QC) was usuallyperformed to ensure that there was no non-physical flow from a low to ahigh pressure point in the system. However, with staff turnover thisimportant QC step is easily ignored and can result in serious violationsat some of the fixed separator nodes.

Error! Reference source not found. shows a hypothetical example with asingle well (Well 1) producing to Platform A via a separator andcommingled downstream with a source producer (Platform B). The combinedproduction from Platform A and Platform B then flows through a 200 km32″ pipeline to a slugcatcher. This system was solved for both the fixedpressure (700 psia separator pressure), shown in the top diagram, andinline separator, shown in the bottom diagram, cases, with the resultingpressures at each node shown as psi and the gas flowrate for eachelement shown as MMscfd along the paths of the pipeline. In thisexample, the fixed separator case shows a pressure discontinuity atPlatform A (an unphysical increase from 700 psia to 902 psia) while theinline separator has no pressure discontinuity. The impact of correctlymodelling the pipeline network is a reduction in production from Well 1because the back pressure is higher than in the fixed pressure separatormodel. This hypothetical example mimics part of the model. For example,if Platform B was originally expected to produce 200 MMscf/d then thepressure immediately downstream of Platform A would have been 620 psiand an initial review by the project team would not have noticed anypressure discontinuity. However, with additional drilling on Platform B,the production increased to about 500 MMscf/d resulting in a pressurediscontinuity in the fixed pressure separator scenario. If these changescoincided with staff turnover, the new staff may not have been aware ofthe need to investigate potential pressure discontinuities in thesystem. To avoid this problem, the IPM of the present embodiment now hasonly inline separators within the network and one fixed pressure node atthe boundary of the production system.

In addition to separators, the surface network may include compressors.The modelling options for a compressor in the GAP model include usingfixed pressure drop (dP), fixed power, reciprocating and performancecurve models. Conventional methods modelled compressors using theperformance curve option defined at their maximum speed. Thiseffectively makes the compressors uncontrollable in the optimizationroutine. A major limitation of this approach is that the solutionproduced by a maximum speed compressor may not be optimum as illustratedby Point A in Error! Reference source not found. In this example,presence of velocity constraints and controllable wells upstream ofcompressors caused difficulty with the network solver. Choking backwells in response to the constraint to reduce the velocity through thecompressor also reduces the inlet pressure. The reduction in the inletpressure causes an increase in the fluid velocity which may potentiallyviolate the flowline velocity constraint. This loop would be repeatedseveral times until either the optimiser finds a solution that meets allthe constraints or until it is unable to find a solution that meets allthe constraints and chooses a solution that meets as many constraints aspossible. The resultant effect is a suboptimal solution (see Point A inError! Reference source not found.) where the model run time isincreased, model stability is compromised, constraints are violated andproduction rate is reduced. The recommendation is to reduce compressorspeed in preference to choking back the wells. The ideal solution is torun the compressors at a speed where the wells are not choked, yet stillhonour the velocity constraint envelope, shown as the Point B in Error!Reference source not found.

In this situation it is necessary to modify the compressor speed tooptimise the performance of the entire system. If the wellhead chokesare also to be optimised then this requires a multi-level optimisationsolution because there are a large number of combinations of wellheadchokes and compressor speeds that produce the same production rate.

Just like the predictive capability of a sub-surface model is dependenton how well it is able to explain the historical performance, theforecasting capability of an integrated model is dependent on itsability to accurately model the pressure drops along the surfacenetwork. Since the fixed pressure separators within the model have beenchanged to inline separators, it has become possible to properlycalibrate the pressure drop within the network. FIG. 7 shows thepressure match for one of the major trunklines in the surface networkbefore calibration 70 and after calibration 71. The field data is shownas dashed lines 73 and 75, the simulated pressure drop data in thesurface network is shown as lines 72 and 74. After calibration, thesimulated pressure drop data for the surface network is much closer tothe field data. FIG. 8 shows that a 30% underprediction in the pressuredrop of one of the major trunklines (solid line 80) can lead to an 18%overprediction of the overall system gas deliverability (dashed line81). Given the importance of the network calibration, the presentembodiment uses the following steps to calibrate the surface network:retrieve daily field production data from the database; if necessary,estimate mass/volume conversion factors; load volumetric rate data as asource in GAP, using appropriate PVT per trunkline when multipletrunklines; consider the daily production for full year—ensure 0%unscheduled production deferment in GAPRun forecast and predict pressuredrop in each trunkline, adjust pipe roughness until dP agrees with fielddata and check that the pipe roughness used in the matching isappropriate.

Step 12 of method 100 combines the subsurface part, well part andsurface network part of the IPM. Difficulties arise here when trying torectify models between the different software used for each part. Forexample, it is possible to parameterize the well part in both GAP andPROSPER; rectifying these is necessary to combine the well part with thesurface network.

FIG. 9 illustrates the discrepancy in production rates when a well modelis not consistent between PROSPER (line 91) and GAP (line 92). In thisexample, the difference is as high as 40 MMscf/d at a constant 3400 psiBHP, as indicated by dashed line 93. One of the reasons for this problemis that the IPR generation method in GAP appears inappropriate for manyhigh rate gas wells. The GAP IPR generation method selects three pointson the IPR contained in PROSPER and then matches the chosen model tothese three points. Unfortunately, the selected points are typically atrates less than 100 MMscfd. For wells that produce up to 360 MMscf/d,this can result in almost 20% error in the predicted gas rates. On theother hand, the IPR matching method contained in MBAL is much moreappropriate because it selects a number of points from the Prosper IPRthat sample the entire curve, not just the first 100 MMScfd, beforefitting an IPR model. To avoid this consistency problem, the presentembodiment uses an IPR model that is present in both GAP and PROSPER andmanually copies the coefficients for the model to GAP and MBAL.

Step 12 of method 100 is also complicated due to human errors. This isnot unexpected given the inadequate documentation of the model, staffturnover in the team and multiple people making changes to differentparts of the model. The following examples illustrate this problem whichrange from mistakes to ignorance. During step 12, quality assurance ofthe model is done to ensure that these errors are identified andcorrected.

It is not uncommon for engineers to rename a tank name during an update.This seemingly innocuous activity can have devastating consequence ifsuch an update disconnects a well from a tank. If a well has a valid IPRand VLP then it will calculate a gas rate regardless of whether it isconnected to a tank or not. The role the tank plays in determining theproduction rate from a well is in updating the well with the reservoirpressure, gas-oil ratio (GOR) and water-gas ratio (WGR). This data isstored on the IPR screen of the well. Consequently, if the wellconnection to the tank is broken, the well will continue to produce at aconstant reservoir pressure. This results in a constant production ratefrom that well. During step 12 of method 100, wells should be examinedto see if this behaviour occurs and be properly integrated into themodel or removed.

Stream day LNG gas demand is limited by the maximum train capacity atthe plant. This is the maximum daily volume of gas that the plant canprocess on any given day. However, there are numerous events during theyear that can reduce this capacity including planned (scheduledmaintenance shutdowns); unplanned (e.g. reliability) and other (e.g.weather) losses. These losses are reflected in an overall downtime valuethat reduces the stream day LNG demand to an annual average value. Toaccurately represent operating conditions and correctly capture thepressure drops in the surface network, it is recommended that separatorsare constrained to produce at the streamday demand rate and a downtimefactor that captures all the losses is also entered into the model.

Constraints are a key method of compelling an integrated model to meetoperational limitations that affect the real asset; howeverinappropriate use of constraints can result in a reduction in modelperformance without any net benefit. A key focus when creating a modelis to ensure that only constraints that can actually be violated areincluded, even if the total list of constraints is much larger.Unfortunately, this was not always the case in conventional methods.Conventional methods generally populated the model with every knownconstraint and this adversely affected the performance of the IPMOptimiser and Solver with its attendant impact on run time. The presentembodiment only the necessary constraints and this has significantlyimproved the performance of the Optimiser and Solver. For example, FIG.10 shows in dark circles, for example 1001, a number of velocityconstraints that have been removed from the model with the necessaryconstraints shown in light circles, for example 1002. Examples of theseredundant constraints include velocity constraints downstream of acompressor when the same constraint is present upstream of thecompressor, minimum pressure constraints, velocity constraints frompipes upstream of an identical pipe with the same constraint and fluidflow rate, or any constraint that expert knowledge suggests will neverbe violated.

Method 100 of FIG. 1 continues to step 13, forecasting hydrocarbonproduction. This may be done, for example, using the IPM suite of PETEX.The present embodiment displays the input data, intermediate productsand final hydrocarbon production forecasting results in a standardisedmanner. This facilitates the quality assurance process and enhancescommunication across the multiple stakeholders. Given the individualneeds of each user company, it is unlikely that any forecasting softwarecan provide the customized visualisation plots for the diverse end usersof the software. The IPM suite is not an exception. However, the IPMsuite offers a link to external software via OpenServer. OpenServer hasthe capability to interface with Excel, different reservoir simulationsoftware, process simulators and general reporting packages. The presentembodiment uses a dashboard that extracts all the IPM input and forecastdata into an Excel spreadsheet underpinned by object-oriented VBA code.The dashboard automatically creates a range of customized plots both forcommunication and quality assurance purposes. FIG. 11 shows sample plotsin the dashboard. The displays may show various production curves formultiple fields 1100 as well as summary production for the entireintegrated production model 1102.

A system 1200 for performing the method is schematically illustrated inFIG. 12. The system includes a data source/storage device 120 which mayinclude, among others, a data storage device or computer memory. Thedevice 120 may contain, for example, production data from one or morefields and/or an initial integrated production model. The data fromdevice 120 may be made available to a processorl21, such as aprogrammable general purpose computer. The processor 121 is configuredto execute computer executable code 122 that can perform the method 100of FIG. 1. These modules may include a subsurface module forparameterizing the subsurface, a well module for parameterizing thewells, a surface network module for parameterizing the surface network,a model improvement module for combining the newly parameterizedsubsurface, wells, and surface network into an improved integratedproduction model, a forecasting module for using the improved IPM toforecast hydrocarbon production, and a display module for preparingdisplays of input, output and intermediary products of the method. Thesystem may include interface components such as user interface 123, andis used to implement the above-described transforms in accordance withembodiments of the invention. The user interface 123 may be used both todisplay data and processed data products and to allow the user to selectamong options for implementing aspects of the method.

While in the foregoing specification this invention has been describedin relation to certain preferred embodiments thereof, and many detailshave been set forth for purpose of illustration, it will be apparent tothose skilled in the art that the invention is susceptible to alterationand that certain other details described herein can vary considerablywithout departing from the basic principles of the invention. Inaddition, it should be appreciated that structural features or methodsteps shown or described in any one embodiment herein can be used inother embodiments as well.

What is claimed is:
 1. A computer-implemented method for improved hydrocarbon production forecasting, the method comprising: a. obtaining, at a computer processor, an initial integrated production model representative of at least two interconnected subsurface tanks, at least one well, and a surface network, wherein the surface network comprises multiple components including at least one pipeline; b. parameterizing, via the computer processor, a subsurface part of the integrated production model by using material balance to characterize the at least two interconnected subsurface tanks; c. parameterizing, via the computer processor, a well part of the integrated production model based in part on well geometry; d. parameterizing, via the computer processor, the surface network based on the multiple components of the surface network; e. combining, via the computer processor, the parameterized subsurface part, the parameterized well part and the parameterized surface network into a reduced-constraint integrated production model wherein the combining comprises removing redundant constraints from at least the parameterized subsurface part or the parameterized well part or the parameterized surface network; and f. forecasting, via the computer processor, hydrocarbon production based on the reduced-constraint integrated production model.
 2. The method of claim 1 wherein the multiple components of the surface network include a fixed pressure separator and at least one other separator.
 3. The method of claim 2 wherein the at least one other separator is an inline separator.
 4. The method of claim 2 wherein the fixed pressure separator and the at least one other separator are constrained to produce at a streamday demand rate.
 5. The method of claim 1 wherein the multiple components of the surface network include at least one compressor.
 6. The method of claim 5 wherein a speed of the at least one compressor is optimized as part of the parameterizing the surface network.
 7. The method of claim 1 wherein the multiple components of the surface network include at least one separator and at least one compressor.
 8. The method of claim 1 further comprising a second subsurface part of the integrated production model that is parameterized separately from the subsurface part, a second well part that is parameterized separately from the well part, and wherein the surface network includes components connected to both the well part and the second well part.
 9. The method of claim 1 wherein the parameterizing the surface network includes a downtime factor that represents planned downtime, unplanned downtime, and weather-related downtime.
 10. The method of claim 1 wherein the parameterizing the surface network includes calibrating the surface network using daily production data.
 11. The method of claim 1 wherein the parameterizing the subsurface part uses a transmissibility factor between the at least two interconnected subsurface tanks to improve reservoir tank pressure history matching.
 12. The method of claim 1 wherein the parameterizing the well part uses water production history matching.
 13. The method of claim 1 wherein the well geometry is vertical, deviated, horizontal or big bore wells.
 14. The method of claim 1 further comprising repeating steps b-f when changes occur to at least one of the material balance, the well geometry, and the multiple components of the surface network.
 15. The method of claim 14 wherein the changes include removing one or more components of at least one of the subsurface part, the well part and the surface network.
 16. The method of claim 14 wherein the changes include replacing one or more components of at least one of the subsurface part, the well part and the surface network.
 17. The method of claim 14 wherein the changes include adding one or more components of at least one of the subsurface part, the well part and the surface network.
 18. A system for improved hydrocarbon production forecasting, the system comprising: a. a data storage device containing an integrated production model and well production data; b. a user-interface device; and c. a computer processor in communication with the data storage device and the user-interface device, the computer processor being designed to receive user input from the user-interface device, to provide visual displays of initial data, intermediate results and final results to the user-interface device, and to execute computer-executable modules, the computer-executable modules comprising: i. a subsurface module for parameterizing a subsurface part of the integrated production model by using material balance to characterize the at least two subsurface tanks; ii. a well module for parameterizing a well part of the integrated production model based in part on well geometry; iii. a surface network module for parameterizing the surface network based on the multiple components of the surface network; iv. a model improvement module for combining the parameterized subsurface part, the parameterized well part and the parameterized surface network into a reduced-constraint integrated production model model wherein the combining comprises removing redundant constraints from at least the parameterized subsurface part or the parameterized well part of the parameterized surface network; v. a forecasting module for forecasting hydrocarbon production based on the improved integrated production model; and vi. a display module for preparing displays of the initial data, the intermediate results and the final results. 